基于神经网络与领域知识的外交国际合作元素抽取

Extraction of diplomatic international cooperation elements based on neural network and domain knowledge

为了能够实时了解国际双边合作中有价值的信息,高效地智能提取Web外交新闻中的国际合作元素就显得至关重要。将国际合作元素抽取抽象为类似命名实体识别的问题,首先,界定国际合作元素的内涵;其次,提取了蕴涵领域知识的规则;再次,结合神经网络与领域知识提出了面向外交新闻文本的国际合作元素抽取方法;最后在相同语料库中与神经网络方法以及自身规则组合进行了比较,实验结果表明该方法具有更好的效果。

In order to get valuable information in bilateral cooperation in real time,it is of utmost importance to efficiently extract international cooperation elements in Web diplomacy news. This paper abstracted the international cooperation element extraction into a problem similar to named entity recognition. First of all,it defined the connotations of international cooperation elements. Secondly,it extracted the rules that contained domain knowledge. Then it proposed a method of extracting international cooperation elements for diplomatic news texts combined with neural network and domain knowledge. Finally,this paper compared the proposed method with the neural network and its own rule combination in the same corpus. The experimental results show that the proposed method has better results.